Diagnostic Performance of 18F-FET PET in Newly Diagnosed Cerebral Lesions Suggestive of Glioma

An effective MRI perfusion threshold based workflow to triage additional 18F-FET PET in posttreatment high grade glioma

MRI is the preferred method for follow-up imaging of post-treatment WHO grade 3 or 4 gliomas. While positron emission tomography with O-(2-[18F]fluoroethyl)-L-tyrosine) (18F-FET PET) offers higher diagnostic accuracy, its use is limited due to low availability. We propose a sequential, threshold-based workflow to triage patients for additional 18F-FET PET scans based on MRI dynamic susceptibility contrast (DSC) perfusion-derived rCBV values, to optimize 18F-FET PET resource allocation. Patients with high-grade gliomas who had undergone standard-of-care treatment and developed new or enlarging contrast-enhancing post-treatment lesions on MRI were included, with a 18F-FET PET study performed within 4 months of the MRI. Patients were excluded if there were significant changes in lesion size or treatment between the MRI and 18F-FET PET scan. An rCBV threshold was determined and the performance of a threshold-based imaging workflow was evaluated compared to the gold standard defined here as surgical verification or long-term imaging follow-up without further intervention. Forty-one patients with a total of 49 lesions were included (tumor progression n = 40, treatment-related changes n = 9). Above the rCBV threshold of 2.4, MRI was 100% accurate (21/21 patients) in diagnosing tumor progression. Below the threshold, MRI identified 9 true negatives but produced 19 false negatives. 18F-FET PET reclassified 18/19 (95%) false negatives resulting in an overall accuracy of 48/49 (98%) for the workflow. Our MRI DSC perfusion rCBV-based threshold workflow for triaging patients for additional 18F-FET PET imaging in post-treatment high grade glioma has the potential to optimize 18F-FET PET resource allocation.

Borderline Findings in O-(2-[18F]-Fluoroethyl)-l-Tyrosine PET of Patients with Suspected Glioma Relapse: Role in Clinical Practice

One of the most common clinical indications for amino acid PET using the tracer O-(2-[18F]-fluoroethyl)-l-tyrosine (18F-FET) is the differentiation of tumor relapse from treatment-related changes in patients with gliomas. A subset of patients may present with an uptake of 18F-FET close to recommended threshold values. The goal of this study was to investigate the frequency of borderline cases and the role of quantitative 18F-FET PET parameters in this situation. Methods: We retrospectively identified 439 patients with pretreated gliomas who underwent 18F-FET PET for suspected tumor relapse and in whom the final diagnoses were confirmed by histopathology (n = 175) or clinical course (n = 264). Two experienced nuclear medicine physicians, masked to the final diagnoses, evaluated visually the PET scans by consensus. The findings were classified into 3 categories: clearly positive findings, borderline findings, or clearly negative findings. The diagnostic performance of established 18F-FET PET parameters (i.e., tumor-to-brain ratio [TBR], time-to-peak ratio, slope, intercept) was evaluated separately for these 3 groups using receiver operating characteristics analyses. Results: In the visual analysis, 18F-FET uptake was classified as clearly negative in 67 patients (15%), clearly positive in 234 patients (53%), and borderline in 136 patients (31%), with averaged mean TBR values of 1.5, 2.3, and 1.9, respectively. Receiver operating characteristics analysis showed a high accuracy for TBR values in patients rated as clearly positive or negative in visual rating (area under curve [AUC], 0.84-0.86), whereas the diagnostic performance of TBR values in borderline cases according to visual analysis was significantly lower (AUC, <0.60). Using TBR values ± 10% above or below the cutoff values increased the AUC by approximately 10% (AUC, 0.82-0.84). Conclusion: A considerable number of patients may present with borderline findings in 18F-FET PET. In these patients, quantitative parameters should be used with caution for decision-making. The use of TBR values above or below the range of the cutoff values ±10% may increase the reliability of quantitative parameters to differentiate between tumor relapse and treatment-related changes.

FET PET to differentiate between post-treatment changes and recurrence in high-grade gliomas: a single center multidisciplinary clinic controlled study

PURPOSE

The clinico-radiological dilemma in post-treatment high-grade gliomas, between disease recurrence (TR) and treatment-related changes (TRC), still persists. FET (Fluoro-ethyl-tyrosine) PET has been extensively used as problem-solving modality for cases where MR imaging is inconclusive. We incorporated a systematic imaging and clinical follow-up algorithm in a multi-disciplinary clinic (MDC) setting to analyse our cohort of FET PET in post-treatment gliomas.

METHODS

We retrospectively analyzed 171 patients of post-treatment grade III and IV glioma with equivocal findings on MRI. 185-222 MBq of 18 F-FET was injected and dedicated static imaging of brain was performed at 20 min. TBR (Tumor to background ratio) was used as semi-quantitative parameter. Cutoff of 2.5 was used for image interpretation. Imaging findings were confirmed with histopathological diagnosis, wherever available or in a multidisciplinary joint clinic based on serial imaging.

RESULTS

121 of 171 patients showed recurrent disease on FET PET, on follow up, 109 were confirmed with recurrence; 7 patients showed TRC, whereas 5 were treated with bevacizumab, with no further clinico-radiological deterioration, thus confirming TRC. 50 patients showed TRC on FET PET, on follow up on follow up, 40 were confirmed as true-negative. 10 patients who showed TBR less than 2.5 had confirmed TR on subsequent MR imaging. The overall sensitivity and specificity was 91.6 and 76.9% respectively, with a diagnostic accuracy of 87.13%.

CONCLUSION

There is potential for FET PET to be used along with MRI in the post treatment algorithm of high-grade glial tumors.

Future Directions in the Treatment of Low-Grade Gliomas

ABSTRACT

There is major interest in deintensifying therapy for isocitrate dehydrogenase-mutant low-grade gliomas, including with single-agent cytostatic isocitrate dehydrogenase inhibitors. These efforts need head-to-head comparisons with proven modalities, such as chemoradiotherapy. Ongoing clinical trials now group tumors by intrinsic molecular subtype, rather than classic clinical risk factors. Advances in imaging, surgery, and radiotherapy have improved outcomes in low-grade gliomas. Emerging biomarkers, targeted therapies, immunotherapy, radionuclides, and novel medical devices are a promising frontier for future treatment. Diverse representation in glioma research and clinical trials will help to ensure that advancements in care are realized by all groups.

Nuclear Medicine Imaging Techniques in Glioblastomas

Glioblastomas are the most common primary malignant grade 4 tumors of the central nervous system (CNS). The treatment and management of such tumors requires a multidisciplinary approach and nuclear medicine techniques play an important role in this process. Glioblastoma, which recurs despite current treatments and becomes resistant to treatments, is among the tumors with the lowest survival rate, with a survival rate of approximately 8 months. Currently, the standard treatment of glioblastoma is adjuvant chemoradiotherapy after surgical resection. There have been many recent advances in the field of Nuclear Medicine in glioblastoma. PET scans are critical in determining tumor localization, pre-surgical planning, evaluation of post-treatment response and detection of recurrence. Advances in the treatment of glioblastoma and a better understanding of the biological characteristics of the disease have contributed to the development of nuclear medicine techniques. This review, in addition to other studies, is intended as a general imaging summary guide and includes some new expressions discovered in glioblastoma. This review discusses recent advances in nuclear medicine in glioblastoma.

11C-Methionine uptake in meningiomas after stereotactic radiotherapy

OBJECTIVE

11C-Methionine positron emission tomography (MET-PET) is used for stereotactic radiotherapy planning in meningioma patients. The role of MET-PET during subsequent follow-up (FU) is unclear. We analyzed the uptake of 11C-Methionine before and after stereotactic radiotherapy (SRT) in patients with a complex meningioma and investigated if there was a difference between patients with progressive disease (PD) and stable disease (SD) during FU.

METHODS

This retrospective study investigates 62 MET-PETs in 29 complex meningioma patients. Standardized uptake value (SUV)max and SUVpeak tumor-to-normal ratios (T/N-ratios) were calculated, comparing the tumor region with both the mirroring intracranial area and the right frontal gray matter. The difference in 11C-Methionine uptake pre- and post-SRT was analyzed, as well as the change in uptake between PD or SD.

RESULTS

Median (IQR) FU duration was 67 months (50.5-91.0). The uptake of 11C-Methionine in meningiomas remained increased after SRT. Neither a statistically significant difference between MET-PETs before and after SRT was encountered, nor a significant difference in one of the four T/N-ratios between patients with SD versus PD with median (IQR) SUVmax T/NR front 2.65 (2.13-3.68) vs 2.97 (1.55-3.54) [p = 0.66]; SUVmax T/Nmirror 2.92 (2.19-3.71) vs 2.95 (1.74-3.60) [p = 0.61]; SUVpeak T/NR front 2.35 (1.64-3.40) vs 2.25 (1.44-3.74) [p = 0.80]; SUVpeak T/Nmirror 2.38 (1.91-3.36) vs 2.35 (1.56-3.72) [p = 0.95].

CONCLUSIONS

Our data do not support use of MET-PET during FU of complex intracranial meningiomas after SRT. MET-PET could not differentiate between progressive or stable disease.

Challenges, limitations, and pitfalls of PET and advanced MRI in patients with brain tumors: A report of the PET/RANO group

Brain tumor diagnostics have significantly evolved with the use of positron emission tomography (PET) and advanced magnetic resonance imaging (MRI) techniques. In addition to anatomical MRI, these modalities may provide valuable information for several clinical applications such as differential diagnosis, delineation of tumor extent, prognostication, differentiation between tumor relapse and treatment-related changes, and the evaluation of response to anticancer therapy. In particular, joint recommendations of the Response Assessment in Neuro-Oncology (RANO) Group, the European Association of Neuro-oncology, and major European and American Nuclear Medicine societies highlighted that the additional clinical value of radiolabeled amino acids compared to anatomical MRI alone is outstanding and that its widespread clinical use should be supported. For advanced MRI and its steadily increasing use in clinical practice, the Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition provided more recently an updated acquisition protocol for the widely used dynamic susceptibility contrast perfusion MRI. Besides amino acid PET and perfusion MRI, other PET tracers and advanced MRI techniques (e.g. MR spectroscopy) are of considerable clinical interest and are increasingly integrated into everyday clinical practice. Nevertheless, these modalities have shortcomings which should be considered in clinical routine. This comprehensive review provides an overview of potential challenges, limitations, and pitfalls associated with PET imaging and advanced MRI techniques in patients with gliomas or brain metastases. Despite these issues, PET imaging and advanced MRI techniques continue to play an indispensable role in brain tumor management. Acknowledging and mitigating these challenges through interdisciplinary collaboration, standardized protocols, and continuous innovation will further enhance the utility of these modalities in guiding optimal patient care.

Impact of improved dead time correction on the quantification accuracy of a dedicated BrainPET scanner

OBJECTIVE

Quantitative values derived from PET brain images are of high interest for neuroscientific applications. Insufficient DT correction (DTC) can lead to a systematic bias of the output parameters obtained by a detailed analysis of the time activity curves (TACs). The DTC method currently used for the Siemens 3T MR BrainPET insert is global, i.e., differences in DT losses between detector blocks are not considered, leading to inaccurate DTC and, consequently, to inaccurate measurements masked by a bias. However, following careful evaluation with phantom measurements, a new block-pairwise DTC method has demonstrated a higher degree of accuracy compared to the global DTC method.

APPROACH

Differences between the global and the block-pairwise DTC method were studied in this work by applying several radioactive tracers. We evaluated the impact on [11C]ABP688, O-(2-[18F]fluoroethyl)-L-tyrosine (FET), and [15O]H2O TACs.

RESULTS

For [11C]ABP688, a relevant bias of between -0.0034 and -0.0053 ml/ (cm3 • min) was found in all studied brain regions for the volume of distribution (VT) when using the current global DTC method. For [18F]FET-PET, differences of up to 10% were observed in the tumor-to-brain ratio (TBRmax), these differences depend on the radial distance of the maximum from the PET isocenter. For [15O]H2O, differences between +4% and -7% were observed in the GM region. Average biases of -4.58%, -3.2%, and -1.2% for the regional cerebral blood flow (CBF (K1)), the rate constant k2, and the volume of distribution VT were observed, respectively. Conversely, in the white matter region, average biases of -4.9%, -7.0%, and 3.8% were observed for CBF (K1), k2, and VT, respectively.

CONCLUSION

The bias introduced by the global DTC method leads to an overestimation in the studied quantitative parameters for all applications compared to the block-pairwise method.

SIGNIFICANCE

The observed differences between the two DTC methods are particularly relevant for research applications in neuroscientific studies as they affect the accuracy of quantitative Brain PET images.

Imaging Role in Diagnosis, Prognosis, and Treatment Response Prediction Associated with High-grade Glioma

Background

Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed.

Materials and Methods

The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings.

Results

Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations.

Conclusion

Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified.

99mTc(CO)3-labeled 1-(2-Pyridyl)piperazine derivatives as radioligands for 5-HT7 receptors

BACKGROUND

The 5-hydroxytryptamine receptor (5-HTR) family includes seven classes of receptors. The 5-HT7R is the newest member of this family and contributes to different physiological and pathological processes. As a pathology, glioblastoma multiform (GBM) overexpresses 5-HT7R; hence, this study aims to develop radiolabeled aryl piperazine derivatives as 5-HT7R imaging agents.  METHODS: Compounds 6 and 7 as 1-(3-nitropyridin-2-yl)piperazine derivatives were radiolabeled with fac-[99mTc(CO)3(H2O)3]+ and 99mTc(CO)3-[6] and 99mTc(CO)3-[7] were obtained with high radiochemical purity (RCP > 94%). The stability of the radiotracers was evaluated in both saline and mouse serum. Specific binding on different cell lines including U-87 MG, MCF-7, SKBR3, and HT-29 was performed. The biodistribution of these radiotracers was evaluated in normal and U-87 MG Xenografted models. Finally, 99mTc(CO)3-[6] and 99mTc(CO)3-[7] were applied for in vivo imaging in U-87 MG Xenografted models.

RESULTS

Specific binding study indicates that 99mTc(CO)3-[6] and 99mTc(CO)3-[7] can recognize 5-HT7R of U87-MG cell line. The biodistribution study in normal mice indicates that the brain uptake of 99mTc(CO)3-[6] and 99mTc(CO)3-[7] is the highest at 30 min post-injection (0.8 ± 0.25 and 0.64 ± 0.18%ID/g, respectively). The data of the biodistribution study in the U87-MG xenograft model revealed that these radiotracers could accumulate in the tumor site, and the highest tumor uptake was observed at 60 min post-injection (3.38 ± 0.65 and 3.27 ± 0.5%ID/g, respectively). The injection of pimozide can block the tumor's radiotracer uptake, indicating the binding of these radiotracers to the 5-HT7R. The imaging study in the xenograft model also confirms the biodistribution data. The acquired images clearly show the tumor site, and the tumor-to-muscle ratio for 99mTc(CO)3-[6] and 99mTc(CO)3-[7] at 60 min was 3.33 and 3.88, respectively.  CONCLUSIONS: 99mTc(CO)3-[6] and 99mTc(CO)3-[7] can visualize tumor in the U87-MG xenograft model  due to their affinity toward 5-HT7R.

Diagnostic Accuracy of MR Spectroscopic Imaging and 18F-FET PET for Identifying Glioma: A Biopsy-Controlled Hybrid PET/MRI Study

Contrast-enhanced MRI is the method of choice for brain tumor diagnostics, despite its low specificity for tumor tissue. This study compared the contribution of MR spectroscopic imaging (MRSI) and amino acid PET to improve the detection of tumor tissue. Methods: In 30 untreated patients with suspected glioma, O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) PET; 3-T MRSI with a short echo time; and fluid-attenuated inversion recovery, T2-weighted, and contrast-enhanced T1-weighted MRI were performed for stereotactic biopsy planning. Serial samples were taken along the needle trajectory, and their masks were projected to the preoperative imaging data. Each sample was individually evaluated neuropathologically. 18F-FET uptake and the MRSI signals choline (Cho), N-acetyl-aspartate (NAA), creatine, myoinositol, and derived ratios were evaluated for each sample and classified using logistic regression. The diagnostic accuracy was evaluated by receiver operating characteristic analysis. Results: On the basis of the neuropathologic evaluation of tissue from 88 stereotactic biopsies, supplemented with 18F-FET PET and MRSI metrics from 20 areas on the healthy-appearing contralateral hemisphere to balance the glioma/nonglioma groups, 18F-FET PET identified glioma with the highest accuracy (area under the receiver operating characteristic curve, 0.89; 95% CI, 0.81-0.93; threshold, 1.4 × background uptake). Among the MR spectroscopic metabolites, Cho/NAA normalized to normal brain tissue showed the highest diagnostic accuracy (area under the receiver operating characteristic curve, 0.81; 95% CI, 0.71-0.88; threshold, 2.2). The combination of 18F-FET PET and normalized Cho/NAA did not improve the diagnostic performance. Conclusion: MRI-based delineation of gliomas should preferably be supplemented by 18F-FET PET.

Delineation and agreement of FET PET biological volumes in glioblastoma: results of the nuclear medicine credentialing program from the prospective, multi-centre trial evaluating FET PET In Glioblastoma (FIG) study-TROG 18.06

PURPOSE

The O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET in Glioblastoma (FIG) trial is an Australian prospective, multi-centre study evaluating FET PET for glioblastoma patient management. FET PET imaging timepoints are pre-chemoradiotherapy (FET1), 1-month post-chemoradiotherapy (FET2), and at suspected progression (FET3). Before participant recruitment, site nuclear medicine physicians (NMPs) underwent credentialing of FET PET delineation and image interpretation.

METHODS

Sites were required to complete contouring and dynamic analysis by ≥ 2 NMPs on benchmarking cases (n = 6) assessing biological tumour volume (BTV) delineation (3 × FET1) and image interpretation (3 × FET3). Data was reviewed by experts and violations noted. BTV definition includes tumour-to-background ratio (TBR) threshold of 1.6 with crescent-shaped background contour in the contralateral normal brain. Recurrence/pseudoprogression interpretation (FET3) required assessment of maximum TBR (TBRmax), dynamic analysis (time activity curve [TAC] type, time to peak), and qualitative assessment. Intraclass correlation coefficient (ICC) assessed volume agreement, coefficient of variation (CoV) compared maximum/mean TBR (TBRmax/TBRmean) across cases, and pairwise analysis assessed spatial (Dice similarity coefficient [DSC]) and boundary agreement (Hausdorff distance [HD], mean absolute surface distance [MASD]).

RESULTS

Data was accrued from 21 NMPs (10 centres, n ≥ 2 each) and 20 underwent review. The initial pass rate was 93/119 (78.2%) and 27/30 requested resubmissions were completed. Violations were found in 25/72 (34.7%; 13/12 minor/major) of FET1 and 22/74 (29.7%; 14/8 minor/major) of FET3 reports. The primary reasons for resubmission were as follows: BTV over-contour (15/30, 50.0%), background placement (8/30, 26.7%), TAC classification (9/30, 30.0%), and image interpretation (7/30, 23.3%). CoV median and range for BTV, TBRmax, and TBRmean were 21.53% (12.00-30.10%), 5.89% (5.01-6.68%), and 5.01% (3.37-6.34%), respectively. BTV agreement was moderate to excellent (ICC = 0.82; 95% CI, 0.63-0.97) with good spatial (DSC = 0.84 ± 0.09) and boundary (HD = 15.78 ± 8.30 mm; MASD = 1.47 ± 1.36 mm) agreement.

CONCLUSION

The FIG study credentialing program has increased expertise across study sites. TBRmax and TBRmean were robust, with considerable variability in BTV delineation and image interpretation observed.

Primary brain tumours in adults

The most frequent adult-type primary CNS tumours are diffuse gliomas, but a large variety of rarer CNS tumour types exists. The classification of these tumours is increasingly based on molecular diagnostics, which is reflected in the extensive molecular foundation of the recent WHO 2021 classification of CNS tumours. Resection as extensive as is safely possible is the cornerstone of treatment in most gliomas, and is now also recommended early in the treatment of patients with radiological evidence of histologically low-grade tumours. For the adult-type diffuse glioma, standard of care is a combination of radiotherapy and chemotherapy. Although treatment with curative intent is not available, combined modality treatment has resulted in long-term survival (>10-20 years) for some patients with isocitrate dehydrogenase (IDH) mutant tumours. Other rarer tumours require tailored approaches, best delivered in specialised centres. Targeted treatments based on molecular alterations still only play a minor role in the treatment landscape of adult-type diffuse glioma, and today are mainly limited to patients with tumours with BRAFV600E (ie, Val600Glu) mutations. Immunotherapy for CNS tumours is still in its infancy, and so far, trials with checkpoint inhibitors and vaccination studies have not shown improvement in patient outcomes in glioblastoma. Current research is focused on improving our understanding of the immunosuppressive tumour environment, the molecular heterogeneity of tumours, and the role of tumour microtube network connections between cells in the tumour microenvironment. These factors all appear to play a role in treatment resistance, and indicate that novel approaches are needed to further improve outcomes of patients with CNS tumours.

Initial Experience of 18 F-FET PET-MR Image Fusion for Evaluation of Recurrent Primary Brain Tumors

Background  An accurate monitoring technique is crucial in brain tumors to choose the best treatment approach after surgery and/or chemoradiation. Radiological assessment of brain tumors is widely based on the magnetic resonance imaging (MRI) modality in this regard; however, MRI criteria are unable to precisely differentiate tumoral tissue from treatment-related changes. This study was conducted to evaluate whether fused MRI and O-(2- 18 F-fluoroethyl)-L-tyrosine ( 18 F-FET) positron emission tomography (PET) can improve the diagnostic accuracy of the practitioners to discriminate treatment-related changes from true recurrence of brain tumor. Methods  We retrospectively analyzed 18 F-FET PET/computed tomography (CT) of 11 patients with histopathologically proven brain tumors that were suspicious for recurrence changes after 3 to 4 months of surgery. All the patients underwent MRI and 18 F-FET PET/CT. As a third assessment, fused 18 F-FET PET/MRI was also acquired. Finally, the diagnostic accuracy of the applied modalities was compared. Results  Eleven patients aged 27 to 73 years with a mean age of 47 ± 13 years were enrolled. According to the results, 9/11 cases (82%) showed positive MRI and 6 cases (55%) showed positive PET/CT and PET/MRI. Tumoral recurrence was observed in six patients (55%) in the follow-up period. Based on the follow-up results, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 64, 85, 25, 67, and 50%, respectively, for MRI alone and 91, 85, 100, 100, and 80%, respectively, for both PET/CT and PET/MRI. Conclusion  This study found that 18 F-FET PET-MR image fusion in the management of brain tumors might improve recurrence detection; however, further well-designed studies are needed to verify these preliminary data.

A multi-label CNN model for the automatic detection and segmentation of gliomas using [18F]FET PET imaging

PURPOSE

The aim of this study was to develop a convolutional neural network (CNN) for the automatic detection and segmentation of gliomas using [18F]fluoroethyl-L-tyrosine ([18F]FET) PET.

METHODS

Ninety-three patients (84 in-house/7 external) who underwent a 20-40-min static [18F]FET PET scan were retrospectively included. Lesions and background regions were defined by two nuclear medicine physicians using the MIM software, such that delineations by one expert reader served as ground truth for training and testing the CNN model, while delineations by the second expert reader were used to evaluate inter-reader agreement. A multi-label CNN was developed to segment the lesion and background region while a single-label CNN was implemented for a lesion-only segmentation. Lesion detectability was evaluated by classifying [18F]FET PET scans as negative when no tumor was segmented and vice versa, while segmentation performance was assessed using the dice similarity coefficient (DSC) and segmented tumor volume. The quantitative accuracy was evaluated using the maximal and mean tumor to mean background uptake ratio (TBRmax/TBRmean). CNN models were trained and tested by a threefold cross-validation (CV) using the in-house data, while the external data was used for an independent evaluation to assess the generalizability of the two CNN models.

RESULTS

Based on the threefold CV, the multi-label CNN model achieved 88.9% sensitivity and 96.5% precision for discriminating between positive and negative [18F]FET PET scans compared to a 35.3% sensitivity and 83.1% precision obtained with the single-label CNN model. In addition, the multi-label CNN allowed an accurate estimation of the maximal/mean lesion and mean background uptake, resulting in an accurate TBRmax/TBRmean estimation compared to a semi-automatic approach. In terms of lesion segmentation, the multi-label CNN model (DSC = 74.6 ± 23.1%) demonstrated equal performance as the single-label CNN model (DSC = 73.7 ± 23.2%) with tumor volumes estimated by the single-label and multi-label model (22.9 ± 23.6 ml and 23.1 ± 24.3 ml, respectively) closely approximating the tumor volumes estimated by the expert reader (24.1 ± 24.4 ml). DSCs of both CNN models were in line with the DSCs by the second expert reader compared with the lesion segmentations by the first expert reader, while detection and segmentation performance of both CNN models as determined with the in-house data were confirmed by the independent evaluation using external data.

CONCLUSION

The proposed multi-label CNN model detected positive [18F]FET PET scans with high sensitivity and precision. Once detected, an accurate tumor segmentation and estimation of background activity was achieved resulting in an automatic and accurate TBRmax/TBRmean estimation, such that user interaction and potential inter-reader variability can be minimized.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 2

Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Prediction of response to lomustine-based chemotherapy in glioma patients at recurrence using MRI and FET PET

BACKGROUND

We evaluated O-(2-[18F]fluoroethyl)-l-tyrosine (FET) PET and MRI for early response assessment in recurrent glioma patients treated with lomustine-based chemotherapy.

METHODS

Thirty-six adult patients with WHO CNS grade 3 or 4 gliomas (glioblastoma, 69%) at recurrence (median number of recurrences, 1; range, 1-3) were retrospectively identified. Besides MRI, serial FET PET scans were performed at baseline and early after chemotherapy initiation (not later than two cycles). Tumor-to-brain ratios (TBR), metabolic tumor volumes (MTV), the occurrence of new distant hotspots with a mean TBR >1.6 at follow-up, and the dynamic parameter time-to-peak were derived from all FET PET scans. PET parameter thresholds were defined using ROC analyses to predict PFS of ≥6 months and OS of ≥12 months. MRI response assessment was based on RANO criteria. The predictive values of FET PET parameters and RANO criteria were subsequently evaluated using univariate and multivariate survival estimates.

RESULTS

After treatment initiation, the median follow-up time was 11 months (range, 3-71 months). Relative changes of TBR, MTV, and RANO criteria predicted a significantly longer PFS (all P ≤ .002) and OS (all P ≤ .045). At follow-up, the occurrence of new distant hotspots (n ≥ 1) predicted a worse outcome, with significantly shorter PFS (P = .005) and OS (P < .001). Time-to-peak changes did not predict a significantly longer survival. Multivariate survival analyses revealed that new distant hotspots at follow-up FET PET were most potent in predicting non-response (P < .001; HR, 8.578).

CONCLUSIONS

Data suggest that FET PET provides complementary information to RANO criteria for response evaluation of lomustine-based chemotherapy early after treatment initiation.

Amino Acid PET in Neurooncology

For decades, several amino acid PET tracers have been used to optimize diagnostics in patients with brain tumors. In clinical routine, the most important clinical indications for amino acid PET in brain tumor patients are differentiation of neoplasm from nonneoplastic etiologies, delineation of tumor extent for further diagnostic and treatment planning (i.e., diagnostic biopsy, resection, or radiotherapy), differentiation of treatment-related changes such as pseudoprogression or radiation necrosis after radiation or chemoradiation from tumor progression at follow-up, and assessment of response to anticancer therapy, including prediction of patient outcome. This continuing education article addresses the diagnostic value of amino acid PET for patients with either glioblastoma or metastatic brain cancer.

Synthesis and evaluation of 99mTc-labeled 1-(2-Pyridyl)piperazine derivatives as radioligands for 5HT7 receptors

Glioblastoma multiform (GBM) is one of the most aggressive tumors of the central nervous system in humans. GBM overexpresses serotonin-7 receptors (5-HT₇Rs); hence, this study aims to develop 5-HT₇R targeted radiotracers. Aryl piperazine derivatives can act as ligands for 5-HT₇R. Therefore, compounds 6 and 7 as 1-(3-nitropyridin-2-yl)piperazine derivatives were synthesized and radiolabeled with ^99mTcN²⁺ core. Radiolabeled 6 and 7 (^99mTcN-[6] and ^99mTcN-[7]) were prepared with high radiochemical purity (RCP > 96%). They displayed high affinity toward U-87 MG cell line 5-HT₇R. The calculated K_i for ^99mTcN-[7] was lower than that of ^99mTcN-[6] (14.85 ± 0.32 vs 22.57 ± 0.73 nM) which indicates the higher affinity of ^99mTcN-[7] toward 5-HT₇R. A molecular docking study also confirmed the binding of these radiotracers to 5-HT₇R. The biodistribution study in normal mice revealed that ^99mTcN-[7] has the highest brain accumulation at 30 min post-injection (0.54 ± 0.12 %ID/g) while the uptake of ^99mTcN-[6] is much lower (0.14 ± 0.02 %ID/g). The biodistribution study in the xenograft model confirms that the radiotracers recognize the tumor site. ^99mTcN-[6], and ^99mTcN-[7] showed the highest tumor uptake at 1-hour post-injection (5.44 ± 0.58 vs 4.94 ± 1.65 %ID/g) and tumor-to-muscle ratios were (4.61 vs. 5.61). The injection of pimozide blocks the receptors and significantly reduces the tumor-to-muscle ratios at 1-hour post-injection to 0.81 and 0.31, respectively. In correlation with in vitro study, ^99mTcN-[6] and ^99mTcN-[7] visualize the tumor site in U-87 MG glioma xenografted nude mice and display the tumor-to-muscle ratios of 7.05 and 6.03.

Therapy Defining at Initial Diagnosis of Primary Brain Tumor-The Role of 18F-FET PET/CT and MRI

Primary malignant brain tumors are heterogeneous and infrequent neoplasms. Their classification, therapeutic regimen and prognosis have undergone significant development requiring the innovation of an imaging diagnostic. The performance of enhanced magnetic resonance imaging depends on blood-brain barrier function. Several studies have demonstrated the advantages of static and dynamic amino acid PET/CT providing accurate metabolic status in the neurooncological setting. The aim of our single-center retrospective study was to test the primary diagnostic role of amino acid PET/CT compared to enhanced MRI. Emphasis was placed on cases prior to intervention, therefore, a certain natural bias was inevitable. In our analysis for newly found brain tumors ¹⁸F-FET PET/CT outperformed contrast MRI and PWI in terms of sensitivity and negative predictive value (100% vs. 52.9% and 36.36%; 100% vs. 38.46% and 41.67%), in terms of positive predictive value their performance was roughly the same (84.21 % vs. 90% and 100%), whereas regarding specificity contrast MRI and PWI were superior (40% vs. 83.33% and 100%). Based on these results the superiority of ¹⁸F-FET PET/CT seems to present incremental value during the initial diagnosis. In the case of non-enhancing tumors, it should always be suggested as a therapy-determining test.

Challenges and opportunities for advanced neuroimaging of glioblastoma

Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.

Clinical applications and prospects of PET imaging in patients with IDH-mutant gliomas

PET imaging using radiolabeled amino acids in addition to MRI has become a valuable diagnostic tool in the clinical management of patients with brain tumors. This review provides a comprehensive overview of PET studies in glioma patients with a mutation in the isocitrate dehydrogenase gene (IDH). A considerable fraction of these tumors typically show no contrast enhancement on MRI, especially when classified as grade 2 according to the World Health Organization classification of Central Nervous System tumors. Major diagnostic challenges in this situation are differential diagnosis, target definition for diagnostic biopsies, delineation of glioma extent for treatment planning, differentiation of treatment-related changes from tumor progression, and the evaluation of response to alkylating agents. The main focus of this review is the role of amino acid PET in this setting. Furthermore, in light of clinical trials using IDH inhibitors targeting the mutated IDH enzyme for treating patients with IDH-mutant gliomas, we also aim to give an outlook on PET probes specifically targeting the IDH mutation, which appear potentially helpful for response assessment.

Clinical Usefulness of 18 F-FET PET in a Pediatric Patient With Suspected Demyelinating Disease

ABSTRACT

An 11-year-old boy who presented with headache and progressive right-sided weakness exhibited cortical swelling in the parafalcine area of both frontoparietal high convexity and splenium portion of corpus callosum on brain MRI. This suggested the possibility of encephalopathy, but required differential diagnosis from brain tumor. 18 F-FET ( O -(2-[ 18 F]fluoroethyl)- l -tyrosine) PET/CT identified increased uptake along the parafalcine area of the frontoparietal lobes and the splenium portion of the corpus callosum. The relatively low target-to-background ratios were more indicative of inflammatory changes such as demyelinating disease. The patient recovered after empirical steroid and immunoglobulin treatment. Clinically, the patient was diagnosed with acute disseminated encephalomyelitis.

Applications of Artificial Intelligence Based on Medical Imaging in Glioma: Current State and Future Challenges

Glioma is one of the most fatal primary brain tumors, and it is well-known for its difficulty in diagnosis and management. Medical imaging techniques such as magnetic resonance imaging (MRI), positron emission tomography (PET), and spectral imaging can efficiently aid physicians in diagnosing, treating, and evaluating patients with gliomas. With the increasing clinical records and digital images, the application of artificial intelligence (AI) based on medical imaging has reduced the burden on physicians treating gliomas even further. This review will classify AI technologies and procedures used in medical imaging analysis. Additionally, we will discuss the applications of AI in glioma, including tumor segmentation and classification, prediction of genetic markers, and prediction of treatment response and prognosis, using MRI, PET, and spectral imaging. Despite the benefits of AI in clinical applications, several issues such as data management, incomprehension, safety, clinical efficacy evaluation, and ethical or legal considerations, remain to be solved. In the future, doctors and researchers should collaborate to solve these issues, with a particular emphasis on interdisciplinary teamwork.

Facts and Fictions About [18F]FDG versus Other Tracers in Managing Patients with Brain Tumors: It Is Time to Rectify the Ongoing Misconceptions

MRI is the first-choice imaging technique for brain tumors. Positron emission tomography can be combined together with multiparametric MRI to increase diagnostic confidence. Radiolabeled amino acids have gained wide clinical acceptance. The reported pooled specificity of [¹⁸F]FDG positron emission tomography is high and [¹⁸F]FDG might still be the first-choice positron emission tomography tracer in cases of World Health Organization grade 3 to 4 gliomas or [¹⁸F]FDG-avid tumors, avoiding the use of more expensive and less available radiolabeled amino acids. The present review discusses the additional value of positron emission tomography with a focus on [¹⁸F]FDG and radiolabeled amino acids.

Role of Molecular Imaging with PET/MR Imaging in the Diagnosis and Management of Brain Tumors

Gliomas are the most common primary brain tumors. Hybrid PET/MR imaging has revolutionized brain tumor imaging, allowing for noninvasive, simultaneous assessment of morphologic, functional, metabolic, and molecular parameters within the brain. Molecular information obtained from PET imaging may aid in the detection, classification, prognostication, and therapeutic decision making for gliomas. ¹⁸F-fluorodeoxyglucose (FDG) has been widely used in the setting of brain tumor imaging, and multiple techniques may be employed to optimize this methodology. More recently, a number of non-¹⁸F-FDG-PET radiotracers have been applied toward brain tumor imaging and are used in clinical practice.

The Use of 18F-FET-PET-MRI in Neuro-Oncology: The Best of Both Worlds—A Narrative Review

Gliomas are the most frequent primary tumors of the brain. They can be divided into grade II-IV astrocytomas and grade II-III oligodendrogliomas, based on their histomolecular profile. The prognosis and treatment is highly dependent on grade and well-identified prognostic and/or predictive molecular markers. Multi-parametric MRI, including diffusion weighted imaging, perfusion, and MR spectroscopy, showed increasing value in the non-invasive characterization of specific molecular subsets of gliomas. Radiolabeled amino-acid analogues, such as 18F-FET, have also been proven valuable in glioma imaging. These tracers not only contribute in the diagnostic process by detecting areas of dedifferentiation in diffuse gliomas, but this technique is also valuable in the follow-up of gliomas, as it can differentiate pseudo-progression from real tumor progression. Since multi-parametric MRI and 18F-FET PET are complementary imaging techniques, there may be a synergistic role for PET-MRI imaging in the neuro-oncological imaging of primary brain tumors. This could be of value for both primary staging, as well as during treatment and follow-up.

Advanced Imaging Techniques for Newly Diagnosed and Recurrent Gliomas

Management of gliomas following initial diagnosis requires thoughtful presurgical planning followed by regular imaging to monitor treatment response and survey for new tumor growth. Traditional MR imaging modalities such as T1 post-contrast and T2-weighted sequences have long been a staple of tumor diagnosis, surgical planning, and post-treatment surveillance. While these sequences remain integral in the management of gliomas, advances in imaging techniques have allowed for a more detailed characterization of tumor characteristics. Advanced MR sequences such as perfusion, diffusion, and susceptibility weighted imaging, as well as PET scans have emerged as valuable tools to inform clinical decision making and provide a non-invasive way to help distinguish between tumor recurrence and pseudoprogression. Furthermore, these advances in imaging have extended to the operating room and assist in making surgical resections safer. Nevertheless, surgery, chemotherapy, and radiation treatment continue to make the interpretation of MR changes difficult for glioma patients. As analytics and machine learning techniques improve, radiomics offers the potential to be more quantitative and personalized in the interpretation of imaging data for gliomas. In this review, we describe the role of these newer imaging modalities during the different stages of management for patients with gliomas, focusing on the pre-operative, post-operative, and surveillance periods. Finally, we discuss radiomics as a means of promoting personalized patient care in the future.

Prognostic value of pre-irradiation FET PET in patients with not completely resectable IDH-wildtype glioma and minimal or absent contrast enhancement

In glioma patients, complete resection of the contrast-enhancing portion is associated with improved survival, which, however, cannot be achieved in a considerable number of patients. Here, we evaluated the prognostic value of O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine (FET) PET in not completely resectable glioma patients with minimal or absent contrast enhancement before temozolomide chemoradiation. Dynamic FET PET scans were performed in 18 newly diagnosed patients with partially resected (n = 8) or biopsied (n = 10) IDH-wildtype astrocytic glioma before initiation of temozolomide chemoradiation. Static and dynamic FET PET parameters, as well as contrast-enhancing volumes on MRI, were calculated. Using receiver operating characteristic analyses, threshold values for which the product of paired values for sensitivity and specificity reached a maximum were obtained. Subsequently, the prognostic values of FET PET parameters and contrast-enhancing volumes on MRI were evaluated using univariate Kaplan–Meier and multivariate Cox regression (including the MTV, age, MGMT promoter methylation, and contrast-enhancing volume) survival analyses for progression-free and overall survival (PFS, OS). On MRI, eight patients had no contrast enhancement; the remaining patients had minimal contrast-enhancing volumes (range, 0.2–5.3 mL). Univariate analyses revealed that smaller pre-irradiation FET PET tumor volumes were significantly correlated with a more favorable PFS (7.9 vs. 4.2 months; threshold, 14.8 mL; P = 0.012) and OS (16.6 vs. 9.0 months; threshold, 23.8 mL; P = 0.002). In contrast, mean tumor-to-brain ratios and time-to-peak values were only associated with a longer PFS (P = 0.048 and P = 0.045, respectively). Furthermore, the pre-irradiation FET PET tumor volume remained significant in multivariate analyses (P = 0.043), indicating an independent predictor for OS. Our results suggest that pre-irradiation FET PET parameters have a prognostic impact in this subgroup of patients.

18F-FET PET/CT as a Diagnostic Tool for Brain Abscess

ABSTRACT

A 49-year-old man presented with sudden right-sided weakness and seizure. Brain MRI identified a lobulated mass with diffusion restriction and irregular wall enhancement in the left parietal lobe. 18F-FET (O-(2-[18F]fluoroethyl)-l-tyrosine) PET/CT was performed, which identified a cystic mass in the left parietal lobe accompanied by FET uptake. Compartmentalized uptake was also confirmed throughout the left parietal lobe. Considering the relatively low target-to-background ratio and uptake observed in the entire left parietal lobe, the lesion was more likely to be a brain abscess than a tumor. The pathologic diagnosis after mass removal was acute and chronic inflammation with abscess.

Repeatability of image features extracted from FET PET in application to post-surgical glioblastoma assessment

Positron emission tomography (PET) imaging using the amino acid tracer O-[2-(¹⁸F)fluoroethyl]-L-tyrosine (FET) has gained increased popularity within the past decade in the management of glioblastoma (GBM). Radiomics features extracted from FET PET images may be sensitive to variations when imaging at multiple time points. It is therefore necessary to assess feature robustness to test-retest imaging. Eight patients with histologically confirmed GBM that had undergone post-surgical test-retest FET PET imaging were recruited. In total, 1578 radiomic features were extracted from biological tumour volumes (BTVs) delineated using a semi-automatic contouring method. Feature repeatability was assessed using the intraclass correlation coefficient (ICC). The effect of both bin width and filter choice on feature repeatability was also investigated. 59/106 (55.7%) features from the original image and 843/1472 (57.3%) features from filtered images had an ICC ≥ 0.85. Shape and first order features were most stable. Choice of bin width showed minimal impact on features defined as stable. The Laplacian of Gaussian (LoG, σ = 5 mm) and Wavelet filters (HLL and LHL) significantly improved feature repeatability (p ≪ 0.0001, p = 0.003, p = 0.002, respectively). Correlation of textural features with tumour volume was reported for transparency. FET PET radiomic features extracted from post-surgical images of GBM patients that are robust to test-retest imaging were identified. An investigation with a larger dataset is warranted to validate the findings in this study.

What is the current clinico-radiological diagnostic accuracy for intracranial tumours?

OBJECTIVE

To determine the diagnostic accuracy of routine clinico-radiological workup for a population-based selection of intracranial tumours.

METHODS

In this prospective cohort study, we included consecutive adult patients who underwent a primary surgical intervention for a suspected intracranial tumour between 2015 and 2019 at a single-neurosurgical centre. The treating team estimated the expected diagnosis prior to surgery using predefined groups. The expected diagnosis was compared to final histopathology and the accuracy of preoperative clinico-radiological diagnosis (sensitivity, specificity, positive and negative predictive values) was calculated.

RESULTS

392 patients were included in the data analysis, of whom 319 underwent a primary surgical resection and 73 were operated with a diagnostic biopsy only. The diagnostic accuracy varied between different tumour types. The overall sensitivity, specificity and diagnostic mismatch rate of clinico-radiological diagnosis was 85.8%, 97.7% and 4.0%, respectively. For gliomas (including differentiation between low-grade and high-grade gliomas), the same diagnostic accuracy measures were found to be 82.2%, 97.2% and 5.6%, respectively. The most common diagnostic mismatch was between low-grade gliomas, high-grade gliomas and metastases. Accuracy of 90.2% was achieved for differentiation between diffuse low-grade gliomas and high-grade gliomas.

CONCLUSIONS

The current accuracy of a preoperative clinico-radiological diagnosis of brain tumours is high. Future non-invasive diagnostic methods need to outperform our results in order to add much value in a routine clinical setting in unselected patients.

Synthesis and Biological Evaluation of 99mTc-Labeled Phenylpiperazine Derivatives as Selective Serotonin-7 Receptor Ligands for Brain Tumor Imaging

With a poor prognosis, glioblastoma multiforme is the most aggressive tumor of the central nervous system in humans. The aim of this study was to develop novel tracers for the tumor targeting and imaging of overexpressed serotonin-7 receptors (5-HT₇Rs) in U-87 MG glioma xenografted nude mice. Two phenylpiperazine derivatives named as PHH and MPHH were designed, and the corresponding radiotracers ^99mTc-PHH and ^99mTc-MPHH were synthesized in high radiochemical purity (>95%). ^99mTc-MPHH showed a higher affinity to 5-HT₇Rs on U-87 MG cells compared to ^99mTc-PHH. In biodistribution studies, the radiocomplexes showed good brain uptake at 15 min combined with good radioactivity retention in the brain for 240 min. Regional rabbit brain studies indicated a higher radioactivity concentration in the hippocampus and diencephalon than in the cerebellum. Compared to ^99mTc-MPHH, the ^99mTc-PHH exhibited a significantly increased tumor uptake at 15 and 60 min, but the rapid blood clearance of ^99mTc-MPHH led to enhanced tumor-to-muscle ratios at 240 min. A significant reduction in tumor uptake 60 min after an injection of pimozide (5-HT₇ receptor antagonist) confirms the tumor uptake was receptor-mediated specifically. The tumor-to-contralateral muscle tissue ratio of ^99mTc-PHH and ^99mTc-MPHH in nude mice with U-87 MG xenograft was measured (5.25 and 4.65) at 60 min as well as (6.25 and 6.76) at 240 min, respectively.

Glioma Biopsy Based on Hybrid Dual Time-Point FET-PET/MRI-A Proof of Concept Study

Neuroimaging based on O-[2-(18F)fluoroethyl]-l-tyrosine (FET)-PET provides additional information on tumor grade and extent compared with MRI. Dynamic PET for biopsy target selection further improves results but is often clinically impractical. Static FET-PET performed at two time-points may be a good compromise, but data on this approach are limited. The aim of this study was to compare the histology of lesions obtained from two challenging glioma patients with targets selected based on hybrid dual time-point FET-PET/MRI. Five neuronavigated tumor biopsies were performed in two difficult cases of suspected glioma. Lesions with (T1-CE) and without contrast enhancement (T1 and T2-FLAIR) on MRI were selected. Dual time-point FET-PET imaging was performed 5–15 min (PET10) and 45–60 min (PET60) after radionuclide injection. The most informative FET-PET/MRI images were coregistered with MRI in time of biopsy planning. Five biopsy targets (three from high uptake and two from moderate uptake FET areas) thought to represent the most malignant sites and tumor extent were selected. Histopathological findings were compared with FET-PET and MRI images. Increased FET uptake in the area of non-CE locations on MRI correlated well with high-grade gliomas localized as far as 3 cm from T1-CE foci. Selecting a target in the motor cortex based on FET kinetics defined by dual time-point PET resulted in a grade IV diagnosis after previous negative biopsies based on MRI. An additional grade III diagnosis was obtained from an area of glioma infiltration with moderate FET uptake (between 1 and 1.25 SUV). These findings seem to show that dual time-point FET-PET-based biopsies can provide additional and clinically useful information for glioma diagnosis. Selection of targets based on dual time-point images may be useful for determining the most malignant tumor areas and may therefore be useful for resection and radiotherapy planning.

Diagnosis of Pseudoprogression Following Lomustine-Temozolomide Chemoradiation in Newly Diagnosed Glioblastoma Patients Using FET-PET

PURPOSE

The CeTeG/NOA-09 phase III trial demonstrated a significant survival benefit of lomustine-temozolomide chemoradiation in patients with newly diagnosed glioblastoma with methylated O⁶-methylguanine-DNA methyltransferase (MGMT) promoter. Following lomustine-temozolomide chemoradiation, late and prolonged pseudoprogression may occur. We here evaluated the value of amino acid PET using O-(2-[¹⁸F]fluoroethyl)-l-tyrosine (FET) for differentiating pseudoprogression from tumor progression.

EXPERIMENTAL DESIGN

We retrospectively identified patients (i) who were treated off-study according to the CeTeG/NOA-09 protocol, (ii) had equivocal MRI findings after radiotherapy, and (iii) underwent additional FET-PET imaging for diagnostic evaluation (number of scans, 1-3). Maximum and mean tumor-to-brain ratios (TBR_max, TBR_mean) and dynamic FET uptake parameters (e.g., time-to-peak) were calculated. In patients with more than one FET-PET scan, relative changes of TBR values were evaluated, that is, an increase or decrease of >10% compared with the reference scan was considered as tumor progression or pseudoprogression. Diagnostic performances were evaluated using ROC curve analyses and Fisher exact test. Diagnoses were confirmed histologically or clinicoradiologically.

RESULTS

We identified 23 patients with 32 FET-PET scans. Within 5-25 weeks after radiotherapy (median time, 9 weeks), pseudoprogression occurred in 11 patients (48%). The parameter TBR_mean calculated from the FET-PET performed 10 ± 7 days after the equivocal MRI showed the highest accuracy (87%) to identify pseudoprogression (threshold, <1.95; P = 0.029). The integration of relative changes of TBR_mean further improved the accuracy (91%; P < 0.001). Moreover, the combination of static and dynamic parameters increased the specificity to 100% (P = 0.005).

CONCLUSIONS

The data suggest that FET-PET parameters are of significant clinical value to diagnose pseudoprogression related to lomustine-temozolomide chemoradiation.

Diagnostic Accuracy and Clinical Impact of [ 18F]FET PET in Childhood CNS tumors

BACKGROUND

Central nervous system (CNS) tumors cause the highest death rates among childhood cancers, and survivors frequently have severe late effects. Magnetic resonance imaging (MRI) is the imaging modality of choice, but its specificity can be challenged by treatment-induced signal changes. In adults, O-(2-[ 18F]fluoroethyl)-L-tyrosine ([ 18F]FET) PET can assist in interpreting MRI findings. We assessed the clinical impact and diagnostic accuracy of adding [ 18F]FET PET to MRI in children with CNS tumors.

METHODS

A total of 169 [ 18F]FET PET scans were performed in 97 prospectively and consecutively included patients with known or suspected childhood CNS tumors. Scans were performed at primary diagnosis, before or after treatment, or at relapse.

RESULTS

Adding [ 18F]FET PET to MRI impacted clinical management in 8% [95% confidence interval (CI): 4-13%] of all scans (n=151) and in 33% [CI: 17-53%] of scans deemed clinically indicated due to difficult decision-making on MRI alone (n=30). Using pathology or follow-up as reference standard, the addition of [ 18F]FET PET increased specificity (1.00 [0.82-1.00] vs. 0.48 [0.30-0.70], p=0.0001) and accuracy (0.91 [CI: 0.87-0.96] vs. 0.81 [CI: 0.75-0.89], p=0.04) in 83 treated lesions and accuracy in 58 untreated lesions (0.96 [CI:0.91-1.00] vs 0.90 [CI:0.82-0.92], p<0.001). Further, in a subset of patients (n=15) [ 18F]FET uptake correlated positively with genomic proliferation index.

CONCLUSIONS

The addition of [ 18F]FET PET to MRI helped discriminate tumor from non-tumor lesions in the largest consecutive cohort of pediatric CNS tumor patients presented to date.

18F-Boramino acid PET/CT in healthy volunteers and glioma patients

PURPOSE

In this work, the safety, biodistribution, and radiation dosimetry of large neutral amino acid transporter type-1 (LAT-1) targeting PET tracer ¹⁸F-trifluorobborate-derived tyrosine (denoted as ¹⁸F-FBY) has been investigated. It is designed as a first-in-human study in healthy volunteers and to assay LAT-1 expression level in glioma patients.

METHODS

Six healthy volunteers (3 M, 3 F) underwent whole-body PET acquisitions at multiple time points after bolus injection of ¹⁸F-FBY. Regions of interest (ROIs) were mapped manually on major organs, and then the time-activity curves (TACs) were obtained. Dosimetry was calculated with the OLINDA/EXM software. Thirteen patients who were suspected of glioma were scanned with PET/CT at 30 min after ¹⁸F-FBY injection. Within 7 days after PET/CT, the tumor was removed surgically, and LAT-1 immunohistochemical staining for LAT-1 was performed on tumor samples and correlated with ¹⁸F-FBY PET imaging.

RESULTS

¹⁸F-FBY was well tolerated by all healthy volunteers, and no adverse symptoms were observed or reported. ¹⁸F-FBY is rapidly cleared from the blood circulation and excreted mainly through the kidneys and urinary tract. The effective dose (ED) was 0.0039 ± 0.0006 mSv/MBq. In 14 surgical confirmed gliomas (one of the patiens had two gliomas), ¹⁸F-FBY uptake increased consistently with tumor grade, with maximum standard uptake values (SUV_max) of 0.28 ± 0.14 and 2.84 ± 0.46 and tumor-to-normal contralateral activity (T/N) ratio of 2.30 ± 1.26 and 24.56 ± 6.32 in low- and high-grade tumors, respectively. In addition to the significant difference in the uptakes between low- and high-grade gliomas (P < 0.001), the immunohistochemical staining confirmed the positive correlations between the SUV_max, LAT-1 expression (r² = 0.80, P < 0.001), and Ki-67 labeling index (r² = 0.79, P < 0.001).

CONCLUSION

¹⁸F-FBY is a PET tracer with favorable dosimetry profile and pharmacokinetics. It has the potential to assay LAT-1 expression in glioma patients and may provide imaging guidance for further boron neutron capture therapy of gliomas.

TRIAL REGISTRATION

clinicaltrials.gov (NCT03980431).

Machine learning-based differentiation between multiple sclerosis and glioma WHO II°-IV° using O-(2-[18F] fluoroethyl)-L-tyrosine positron emission tomography

INTRODUCTION

This study aimed to test the diagnostic significance of FET-PET imaging combined with machine learning for the differentiation between multiple sclerosis (MS) and glioma II°-IV°.

METHODS

Our database was screened for patients in whom FET-PET imaging was performed for the diagnostic workup of newly diagnosed lesions evident on MRI and suggestive of glioma. Among those, we identified patients with histologically confirmed glioma II°-IV°, and those who later turned out to have MS. For each group, tumor-to-brain ratio (TBR) derived features of FET were determined. A support vector machine (SVM) based machine learning algorithm was constructed to enhance classification ability, and Receiver Operating Characteristic (ROC) analysis with area under the curve (AUC) metric served to ascertain model performance.

RESULTS

A total of 41 patients met selection criteria, including seven patients with MS and 34 patients with glioma. TBR values were significantly higher in the glioma group (TBRmax glioma vs. MS: p = 0.002; TBRmean glioma vs. MS: p = 0.014). In a subgroup analysis, TBR values significantly differentiated between MS and glioblastoma (TBRmax glioblastoma vs. MS: p = 0.0003, TBRmean glioblastoma vs. MS: p = 0.0003) and between MS and oligodendroglioma (ODG) (TBRmax ODG vs. MS: p = 0.003; TBRmean ODG vs. MS: p = 0.01). The ability to differentiate between MS and glioma II°-IV° increased from 0.79 using standard TBR analysis to 0.94 using a SVM based machine learning algorithm.

CONCLUSIONS

FET-PET imaging may help differentiate MS from glioma II°-IV° and SVM based machine learning approaches can enhance classification performance.

[18F]FET PET Uptake Indicates High Tumor and Low Necrosis Content in Brain Metastasis

Simple Summary

Various types of cancers can lead to brain metastasis. Treatment strategies have improved substantially in the past decade, leading to longer survival in many cases, but also to new diagnostic challenges. Being able to locate those parts of a lesion suspicious for brain metastasis that contain the highest concentrations of viable tumor cells can be crucial, e.g., to obtain a precise diagnosis via targeted biopsies or to differentiate recurring tumor from dead tissue after treatment. Positron emission tomography (PET) imaging has the potential to provide this kind of information. However, studies relating PET findings to actual tissue properties are sparse. The aim of this study was to investigate the association of PET imaging with microscopic tissue properties in samples obtained neurosurgically from brain metastases. Our findings can improve the planning and yield of biopsies from brain metastases, and they may inform future studies aimed at improving the discrimination of recurring from dead tumor in treated brain metastases using PET.

Abstract

Amino acid positron emission tomography (PET) has been employed in the management of brain metastases. Yet, histopathological correlates of PET findings remain poorly understood. We investigated the relationship of O-(2-[¹⁸F]Fluoroethyl)-L-tyrosine ([¹⁸F]FET) PET, magnetic resonance imaging (MRI), and histology in brain metastases. Fifteen patients undergoing brain metastasis resection were included prospectively. Using intraoperative navigation, 39 targeted biopsies were obtained from parts of the metastases that were either PET-positive or negative and MRI-positive or negative. Tumor and necrosis content, proliferation index, lymphocyte infiltration, and vascularization were determined histopathologically. [¹⁸F]FET PET had higher specificity than MRI (66% vs. 56%) and increased sensitivity for tumor from 73% to 93% when combined with MRI. Tumor content per sample increased with PET uptake (r_s = 0.3, p = 0.045), whereas necrosis content decreased (r_s = −0.4, p = 0.014). PET-positive samples had more tumor (median: 75%; interquartile range: 10–97%; p = 0.016) than PET-negative samples. The other investigated histological properties were not correlated with [¹⁸F]FET PET intensity. Tumors were heterogeneous at the levels of imaging and histology. [¹⁸F]FET PET can be a valuable tool in the management of brain metastases. In biopsies, one should aim for PET hotspots to increase the chance for retrieval of samples with high tumor cell concentrations. Multiple biopsies should be performed to account for intra-tumor heterogeneity. PET could be useful for differentiating treatment-related changes (e.g., radiation necrosis) from tumor recurrence.

Heterogeneous parameters based on 18F-FET PET imaging can non-invasively predict tumor grade and isocitrate dehydrogenase gene 1 mutation in untreated gliomas

Background

The present study aimed to explore the efficacy of easily obtained intratumoral heterogeneous parameters, other than regular semi-quantitative parameters, based on static O-(2-[18F]fluoroethyl)-l-tyrosine (¹⁸F-FET) positron emission tomography (PET) imaging in glioma grade and isocitrate dehydrogenase (IDH) gene 1 mutation prediction.

Methods

Fifty-eight adult patients with untreated glioma (grades II-IV) who underwent preoperative ¹⁸F-FET PET/computed tomography (CT) imaging were enrolled in the present study. Eight semi-automatically obtained static PET imaging parameters after lesion delineation were chosen for analysis. These were: maximal tumor-to-background ratio (TBRmax), peak tumor-to-background ratio (TBRpeak), mean tumor-to-background ratio (TBRmean), coefficient of variation (COV), heterogeneity index (HI), the standard deviation of lesion standardized uptake value (SUVsd), metabolic tumor volume (MTV), and total lesion tracer standardized uptake (TLU). Pathological and immunohistochemical results were used as a reference. The receiver-operating characteristic analysis was used to investigate the predictive efficacy of these parameters in glioma grade and IDH1 mutation status.

Results

TLU [area under the curve (AUC): 0.841, P<0.0001], TBRpeak (AUC: 0.832, P<0.0001), and HI (AUC: 0.826, P<0.0001) had the top 3 single-parameter predictive performance between grade II or III and grade IV glioma patients. Combinations of TBRmax, SUVsd, and TBRmean (AUC: 0.850, P<0.0001); HI, SUVsd, and MTV (AUC: 0.848, P<0.0001); and HI, SUVsd, and TLU (AUC: 0.848, P<0.0001) had the top 3 multiple-parameter predictive performance. SUVsd (AUC: 0.710, P=0.0028), TLU (AUC: 0.698, P=0.0074), and HI (AUC: 0.676, P=0.0159) had the top 3 single-parameter predictive performance in the IDH1 genotype. Combinations of TBRmax, SUVsd, and TBRmean (AUC: 0.821, P<0.0001); SUVsd and TBRmean (AUC: 0.804, P<0.0001); and SUVsd, HI, and TBRmean (AUC: 0.799, P<0.0001) had the top 3 multiple-parameter predictive performance.

Conclusions

These easily obtained and highly repetitive heterogeneous parameters based on static ¹⁸F-FET PET/CT imaging can non-invasively predict glioma grade and IDH1 mutation, crucial in treatment planning, and prognostic evaluation.

Current trends in the use of O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) in neurooncology

The diagnostic potential of PET using the amino acid analogue O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) in brain tumor diagnostics has been proven in many studies during the last two decades and is still the subject of multiple studies every year. In addition to standard magnetic resonance imaging (MRI), positron emission tomography (PET) using [18F]FET provides important diagnostic data concerning brain tumor delineation, therapy planning, treatment monitoring, and improved differentiation between treatment-related changes and tumor recurrence. The pharmacokinetics, uptake mechanisms and metabolism have been well described in various preclinical studies. The accumulation of [18F]FET in most benign lesions and healthy brain tissue has been shown to be low, thus providing a high contrast between tumor tissue and benign tissue alterations. Based on logistic advantages of F-18 labelling and convincing clinical results, [18F]FET has widely replaced short lived amino acid tracers such as L-[11C]methyl-methionine ([11C]MET) in many centers across Western Europe. This review summarizes the basic knowledge on [18F]FET and its contribution to the care of patients with brain tumors. In particular, recent studies about specificity, possible pitfalls, and the utility of [18F]FET PET in tumor grading and prognostication regarding the revised WHO classification of brain tumors are addressed.

[Anaplastic astrocytoma and anaplastic oligodendroglioma of the brain: current state of the problem]

This review is devoted to the problem of anaplastic cerebral gliomas. The authors consider classification, neuroimaging of these tumors including comparison of magnetic resonance imaging and positron emission tomography data. Clinical manifestations of anaplastic gliomas, issues of their histological and molecular genetic classification are discussed. Moreover, the authors compare the data of neuroimaging and genetic examinations of tumors. Other issues are multicomponent treatment and prognosis in patients with anaplastic glioma of the brain.

Static 18F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status

OBJECTIVES

To investigate the predictive value of static O-(2-¹⁸F-fluoroethyl)-L-tyrosine positron emission tomography (¹⁸F-FET PET) and cerebral blood volume (CBV) for glioma grading and determining isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status.

METHODS

Fifty-two patients with newly diagnosed gliomas who underwent simultaneous ¹⁸F-FET PET and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) examinations on hybrid PET/MR were retrospectively enrolled. The mean and max tumor-to-brain ratio (TBR) and normalized CBV (nCBV) were calculated based on whole tumor volume segmentations with reference to PET/MR images. The predictive efficacy of FET PET and CBV in glioma according to the 2016 World Health Organization (WHO) classification was evaluated by receiver operating characteristic curve analyses with the area under the curve (AUC).

RESULTS

TBRmean, TBRmax, nCBVmean, and nCBVmax differed between low- and high-grade gliomas, with the highest AUC of nCBVmean (0.920). TBRmax and nCBVmean showed significant differences between gliomas with and without IDH mutation (p = 0.032 and 0.010, respectively). Furthermore, TBRmean, TBRmax, and nCBVmean discriminated between IDH-wildtype glioblastomas and IDH-mutated astrocytomas (p = 0.049, 0.034 and 0.029, respectively). The combination of TBRmax and nCBVmean showed the best predictive performance (AUC, 0.903). Only nCBVmean differentiated IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas (p < 0.001) (AUC, 0.829), but none of the parameters discriminated between oligodendrogliomas and astrocytomas.

CONCLUSIONS

Both FET PET and DSC-PWI might be non-invasive predictors for glioma grades and IDH mutation status. FET PET combined with CBV could improve the differentiation of IDH-mutated astrocytomas and IDH-wildtype glioblastomas. However, FET PET and CBV might be limited for identifying oligodendrogliomas.

KEY POINTS

• Static ¹⁸F-FET PET and DSC-PWI parameters differed between low- and high-grade gliomas, with the highest AUC of the mean value of normalized CBV. • Static ¹⁸F-FET PET and DSC-PWI parameters based on hybrid PET/MR showed predictive value in identifying glioma IDH mutation subtypes, which have gained importance for both determining the diagnosis and prognosis of gliomas according to the 2016 WHO classification. • Static ¹⁸F-FET PET and DSC-PWI parameters have limited potential in differentiating IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas or IDH-mutated astrocytomas.

Prognostic value of O-(2-[18F]-fluoroethyl)-L-tyrosine PET in relapsing oligodendroglioma

PURPOSE

To assess the relationship between F-18-fluoro-ethyl-tyrosine positron emission tomography (FET-PET) parameters of relapsing oligodendroglioma and progression-free survival.

MATERIAL AND METHODS

The relationship of clinical parameters, FET-PET parameters (SUV_max, TBR_max, BTV_, time-activity curves) and progression-free survival was analyzed using univariate and multivariate analysis in 42 adult patients with relapsing oligodendroglioma. Kaplan-Meier analysis was used to assess survival.

RESULTS

Patients who did not undergo surgical resection of their relapsing tumor had significantly lower PFS if the tumor exhibited an SUV_max above 3.40 than those with an SUV_max below 3.40 (13.1 ± 2.3 months vs. 47.3 ± 6.0 months, respectively, p < .001). Patients who underwent surgery had similar PFS as the aforementioned non-operated patients with low SUV_max (53.6 ± 6.7 months, p = .948). The same was true for TBR_max using a threshold of 3.03 (PFS 12.5 ± 2.4 months vs. 44.0 ± 6.3 months / 53.6 ± 6.7 months, respectively; p < .001 / p = .825). Also, subjects with BTV below 10 cm³ that did not undergo surgery had a similar PFS as subjects who underwent surgery (40.2 ± 6.0 months vs. 52.4 ± 8.9 months, respectively, p = .587). Subjects with BTV above 10 cm³ and without surgery had a significantly worse PFS (13.8 ± 3.3 months, p < .001). Multivariate analysis showed that the prognostication by clinical parameters is improved by adding TBR_max to the model (AUC 0.945 (95% CI: 0.881-1.000), true classification rate 88.1%).

CONCLUSION

FET-PET may provide added value for the prognostication of relapsing oligodendroglioma in addition to clinical parameters.

A Preliminary Study on Machine Learning-Based Evaluation of Static and Dynamic FET-PET for the Detection of Pseudoprogression in Patients with IDH-Wildtype Glioblastoma

Simple Summary

Pseudoprogression detection in glioblastoma patients remains a challenging task. Although pseudoprogression has only a moderate prevalence of 10–30% following first-line treatment of glioblastoma patients, it bears critical implications for affected patients. Non-invasive techniques, such as amino acid PET imaging using the tracer O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine (FET), expose features that have been shown to provide useful information to distinguish tumor progression from pseudoprogression. The usefulness of FET-PET in IDH-wildtype glioblastoma exclusively, however, has not been investigated so far. Recently, machine learning (ML) algorithms have been shown to offer great potential particularly when multiparametric data is available. In this preliminary study, a Linear Discriminant Analysis-based ML algorithm was deployed in a cohort of newly diagnosed IDH-wildtype glioblastoma patients (n = 44) and demonstrated a significantly better diagnostic performance than conventional ROC analysis. This preliminary study is the first to assess the performance of ML in FET-PET for diagnosing pseudoprogression exclusively in IDH-wildtype glioblastoma and demonstrates its potential.

Abstract

Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of PET using O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma. We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. Contrast-enhanced MRI suspected PSP/TP and all patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. We trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a hold-out validation set. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve. Of the 44 patients included in this preliminary study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p = 0.014 and p = 0.033, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax. This preliminary study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance.

18F-FDOPA-PET in pseudotumoral brain lesions

INTRODUCTION

3,4-Dihydroxy-6-[¹⁸F]-fluoro-L-phenylalanine (FDOPA) positron emission tomography (PET) is sensitive for identifying primary brain tumors. However, increased FDOPA uptake has been reported in pseudotumoral brain lesions. Our aim was to analyse FDOPA-PET in patients with pseudotumoral brain lesions and to compare them with patients with brain tumors.

METHODS

We retrospectively analysed consecutively recruited patients with suspected primary brain tumor (based on clinical and magnetic resonance imaging findings) referred for FDOPA-PET in our centre between November 2013 and June 2019 (n = 74). FDOPA-PET parameters (maximum and mean lesion standardised uptake values [SUV] and ratios comparing lesion with different background uptake SUV) and thresholds were evaluated to determine which offered optimal discrimination between pseudotumoral and tumoral lesions.

RESULTS

Overlapping PET values were observed between pseudotumoral (n = 26) and tumoral (n = 48) lesion, particularly for low-grade tumors. Based on receiver operating characteristic (ROC) analyses, the optimal PET parameters to discriminate pseudotumoral from tumoral lesions were SUV_max lesion/basal ganglia, SUV_max lesion/grey matter, SUV_mean lesion/grey matter, and SUV_max lesion/mirror area in contralateral hemisphere (all ratios showing area under the curve [AUC] 0.85, 95% CI). The narrowest 95% sensitivity-95% specificity window was observed for SUV_max lesion/basal ganglia ratio, with ratio values of 0.79 and 1.35 corresponding to 95% sensitivity and 95% specificity, respectively.

CONCLUSION

FDOPA-PET uptake should be interpreted with caution in patients with suspected primary brain tumor, especially in patients showing low or intermediate SUV values and ratios. CLINICAL TRIAL REGISTRATION-URL: https://www.clinicaltrials.gov . Unique identifier: NCT04306484.

Non-FDG PET/CT

The major applications for molecular imaging with PET in clinical practice concern cancer imaging. Undoubtedly, 18F-FDG represents the backbone of nuclear oncology as it remains so far the most widely employed positron emitter compound. The acquired knowledge on cancer features, however, allowed the recognition in the last decades of multiple metabolic or pathogenic pathways within the cancer cells, which stimulated the development of novel radiopharmaceuticals. An endless list of PET tracers, substantially covering all hallmarks of cancer, has entered clinical routine or is being investigated in diagnostic trials. Some of them guard significant clinical applications, whereas others mostly bear a huge potential. This chapter summarizes a selected list of non-FDG PET tracers, described based on their introduction into and impact on clinical practice.